Conclusion générale
A.2 Autres objets
Figure A.1: (a)
(d) (e)
Figure A.2: Quelques modèles géométriques d’objets simulés : (a) Cube, (b) Torus, (c) Ellipsoïde, (d) Récif artificiel (type 1) et (e) Récif artificiel (type 2)
Annexe B
B.1 Le B-scan
– Définition
Un vecteur 1D qui est la somme des colonnes de l’image qui renferment une partie de la réponse de la cible.
– Objectif
Enrichir l’A-scan par une information supplémentaire sur la deuxième dimension
B.2 Combinaison du traitement sur A-scan et B-scan
B.2.1 Limites de la corrélation 1D : Cas de l’ambiguïté MC/MMLa corrélation des A-scans en 1D peut avoir des limites qu’on a pu constaté sur une ambiguïté entre la MC inclinée et la MM (3ème
cas d’ambiguïté (Ligne 3 du Tab5.6)). Nous rappelons dans la figureB.2les résultats du filtrage adapté pour la configuration du cylindre schématisée en haut de la figure.
En utilisant l’A-scan uniquement, nous étions obligés d’aller jusqu’à l’ajout de nou-veaux gabarits pour corriger cette ambiguïté. C’est un traitement conséquent puisqu’il est récursif et fait recours à la simulation.
Figure B.1:B-scan d’une sphère de rayon a = 0.5m
Figure B.2: Résultat du filtrage adapté appliqué à l’A-scan test (au milieu) : L1 le maximum de corrélation de la classe la plus probable (à droite) et L2 est celui de la
classe suivante (à gauche)
En revanche, nous remarquons que le B-scan calculée sur la deuxième dimension a beaucoup de chance de départager la MC de la MM.
Pour vérifier ceci, nous avons ajouté un coefficient de corrélation calculé sur les B-scans.
B.2.2 Apport de la fusion A-scan/B-scan
En plus du filtrage adapté appliqué dans la phase 1 sur les A-scans, nous appliquons de nouveau un filtrage adapté entre le B-scan test et chacun des B-scans ambigus. Nous prenons ensuite la moyenne de ces deux coefficients.
La procédure complète est donnée par les figuresB.3 etB.4.
Le nouveaux critère qui est la moyenne des coefficients de corrélation a bien résolu l’ambiguïté sans avoir besoin de passe par toutes les phases de gestion d’ambiguïté. Ces premiers résultats obtenus en combinant l’A-scan et le B-scan méritent d’être étudiés davantage en vue de généraliser l’apport de cette fusion.
Figure B.3:Résultat du filtrage adapté appliqué entre les B-scans (dernière colonne). En haut : le B-scan test et en bas : celui de la configuration initialement plus probable
Figure B.4:Résultat du filtrage adapté appliqué entre les B-scans (dernière colonne). En haut : le B-scan test et en bas : celui de la configuration initialement moins probable
[AFD97] Tom Aridgides, Manuel Frenandez, and Gerald Dobeck. Adaptive 3di mensional range-crossrange-frequency filter processing string for sea mine classification in side-scan sonar imagery. In SPIE Proc, volume 3079, 1997.
[AFD01] Tom Aridgides, M Fernandez, and G Dobeck. Fusion of adaptive algo-rithms for the classification of sea mines using high resolution side scan sonar in very shallow water. In OCEANS, 2001. MTS/IEEE Conference and Exhibition, volume 1, pages 135–142. IEEE, 2001.
[ASYHD00] Mahmood R Azimi-Sadjadi, De Yao, Qiang Huang, and Gerald J Do-beck. Underwater target classification using wavelet packets and neu-ral networks. Neuneu-ral Networks, IEEE Transactions on, 11(3) :784–794, 2000.
[Bel95] Judith M Bell. A model for the simulation of sidescan sonar. PhD thesis, Heriot-Watt University, 1995.
[Ben12] Yacine Bennani. Signature Electromagnétique Bistatique d’une cible complexe intégrée dans son environnement. Application à l’imagerie ISAR d’une scène maritime. PhD thesis, Université de Bretagne Occi-dentale, 2012.
[Ber08] Cécile Berron. Potentialités de l’inversion géoacoustique de données multicapteurs de sonars cartographiques pour la caractérisation des fonds marins. PhD thesis, Université de Bretagne Occidentale, 2008. [BL97] Judith M Bell and LM Linnett. Simulation and analysis of synthetic
sidescan sonar images. Radar, Sonar and Navigation, IEE Proceedings-, 144(4) :219–226, 1997.
[BMHM12] Richard Brind, Patrick Macey, David Hardie, and Jen Muggleton. Mo-delling the scattering of interface waves by mines in the surf zone. In Proceedings of Meetings on Acoustics, volume 17, page 070047, 2012.
[BMKSP13] T Binesh, M. H Mohankumar Ksupriya, and P.R. Saseendran Pillai. Un-derwater target classifier using a modified transform based feature set. International Journal of Electronics and Communication Engineering (IJECE), 2(3) :21–32, 2013.
[Bou92] Michel Bouvet. Traitements des signaux pour les systèmes sonar. Mas-son, 1992.
[Bou06] Géraldine Bouchage. Modélisation de la propagation basse fréquence par petits fonds : prise en compte de la réverbération et influence des ondes internes. PhD thesis, Université de Bretagne Occidentale, 2006. [BPL+07] J Bell, Y Petillot, K Lebart, PY Mignotte, E Coiras, and H Rohou.
Adaptive fusion architecture for context aware detection and classifica-tion. In OCEANS 2007-Europe, pages 1–6. IEEE, 2007.
[BT97] Shira Lynn Broschat and Eric I Thorsos. An investigation of the small slope approximation for scattering from rough surfaces. part ii. numeri-cal studies. The Journal of the Acoustinumeri-cal Society of America, 101 :2615, 1997.
[BU68] JP Buckley and RJ Urick. Backscattering from the deep sea bed at small grazing angles. The Journal of the Acoustical Society of America, 44 :648, 1968.
[Buc92] Michael J Buckingham. Ocean-acoustic propagation models. J. Acous-tique, 3 :223–287, 1992.
[Bur82] J Burczynski. Introduction à l’utilisation des systèmes SONAR dans l’estimation de la biomasse en poissons : Rév. 1, volume 191. FAO, 1982.
[Cat12] A.T Catherall. High frequency target echo strength prediction using combined kirchhoff and ray tracing methods. ECUA 2012, 2012. [CFMD08] M Couillard, JA Fawcett, V Myers, and M Davison. Support vector
ma-chines for classification of underwater targets in sidescan sonar imagery. Defence R&D Canada Atlantic, Halifax, NS, Canada, Tech. Memo. TM, 190 :2008, 2008.
[CG09] E. Coiras and J. Groen. Simulation and 3d reconstruction of side-looking sonar images nato undersea research centre (nurc). Advances in Sonar Technology, Sergio Rui Silva (Ed.), ISBN : 978-3-902613-48-6, InTech, DOI : 10.5772/39406., 2009.
[CH62] RP Chapman and JH Harris. Surface backscattering strengths measured with explosive sound sources. The Journal of the Acoustical Society of America, 34 :1592, 1962.
[CH00] Charles M Ciany and Jim Huang. Computer aided detection/computer aided classification and data fusion algorithms for automated detection and classification of underwater mines. In OCEANS 2000 MTS/IEEE Conference and Exhibition, volume 1, pages 277–284. IEEE, 2000. [Cha08] Philip Chapple. Automated detection and classification in
high-resolution sonar imagery for autonomous underwater vehicle operations. Technical report, DTIC Document, 2008.
[CJL+06] Vincent Creuze, Bruno Jouvencel, Lionel Lapierre, et al. Analyse des échos de signaux acoustiques diffractés pour le suivi de fond des véhi-cules autonomes sous-marins. In IEEE CIFA’06 : Conférence Interna-tionale Francophone d’Automatique, pages 150–155, 2006.
[CM77] CS Clay and H Medwin. Acoustical oceanography, 544, 1977.
[CMP+07] E Coiras, P-Y Mignotte, Y Petillot, J Bell, and K Lebart. Supervi-sed target detection and classification by training on augmented reality data. Radar, Sonar & Navigation, IET, 1(1) :83–90, 2007.
[CN93] J.W Caruthers and J.C Novarini. Acoustic classification and mapping of the seabed. In Proc. of the Institute of Acoustics, pages 261–270, 1993.
[CPC84] Robert L Cook, Thomas Porter, and Loren Carpenter. Distributed ray tracing. 18(3) :137–145, 1984.
[DBL08] Esther Dura, Judith Bell, and Dave Lane. Superellipse fitting for the recovery and classification of mine-like shapes in sidescan sonar images. Oceanic Engineering, IEEE Journal of, 33(4) :434–444, 2008.
[Dey02] Nicolas Dey. Etude de la formation de l’image d’un objet microsco-pique 3D translucide : application à la microscopie optique. PhD thesis, Université de Nice - Sophia Antipolis, 2002.
[DG74] Vincent A Del Grosso. New equation for the speed of sound in natu-ral waters (with comparisons to other equations). The Journal of the Acoustical Society of America, 56 :1084, 1974.
[DGM98] Sylvie Daniel, Didier Gueriot, and Eric P Maillard. Underwater envi-ronment restitution through sonar images and swath bathymetry rende-ring. In Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on, volume 5, pages 4417–4422. IEEE, 1998.
[DH67] K Jerome Diercks and Robert Hickling. Echoes from hollow aluminum spheres in water. The Journal of the Acoustical Society of America, 41 :380, 1967.
[DH+97] Gerald J Dobeck, John C Hyland, et al. Automated detection and classification of sea mines in sonar imagery. In AeroSense’97, pages 90–110. International Society for Optics and Photonics, 1997.
[Don94] David L. Donoho. De-noising by soft-thresholding, 1994.
[DRVCGE09] J. Del Rio Vera, E. Coiras, J. Groen, and B. Evans. Automatic target recognition in synthetic aperture sonar images based on geometrical feature extraction. EURASIP J. Adv. Signal Process, 2009, January 2009.
[Dut01] Philip Dutré. Global illumination compendium. Cornell University, 2001.
[EB98] GR Elston and JM Bell. Using finite-difference time-domain methods to model sonar data in complex environment. Proc. of the Institute Of Acoustics, pages 69–76, 1998.
[EBQZS13a] Ayda El Bergui, Isabelle Quidu, Benoit Zerr, and Basel Solaiman. Amé-lioration d’une méthode de classification de mines sous-marines utilisant l’écho acoustique dans des images sonar latéral. In TAIMA ’13, pages 1 – 10, 2013.
[EBQZS13b] Ayda El Bergui, Isabelle Quidu, Benoit Zerr, and Basel Solaiman. Model based classification of mine-like objects in sidescan sonar using the high-light information. In Proceedings of Meetings on Acoustics, volume 17, page 070072, 2013.
[Ehr03] A Ehrhold. L’application du sonar à balayage latéral (sbl) pour la car-tographie des habitats marins en domaine subtidal. REBENT, Carto-graphie des peuplements macro-benthiques par les méthodes acoustiques en domaine subtidal, 2003.
[EQZ+11] Ayda Elbergui, Isabelle Quidu, Benoit Zerr, et al. Model based target classification for high frequency–high resolution imaging sonar. Proc. 4th UAM, Kos, Greece, 2011.
[Ett12] Paul C Etter. Advanced applications for underwater acoustic modeling. Advances in Acoustics and Vibration, 2012, 2012.
[Faw01] JA Fawcett. Modeling of high-frequency scattering from objects using a hybrid kirchhoff/diffraction approach. The Journal of the Acoustical Society of America, 109 :1312, 2001.
[Faw03] John A Fawcett. Computer-aided detection and classification of minelike objects using template-based features. In OCEANS 2003. Proceedings, volume 3, pages 1395–1401. IEEE, 2003.
[FCH+07] J Fawcett, A Crawford, D Hopkin, M Couillard, V Myers, and Be-noit Zerr. Computer-aided classification of the citadel trial sidescan so-nar images. Defence Research and Development Canada Atlantic TM, 162 :2007, 2007.
[FFM98] John A Fawcett, WLJ Fox, and A Maguer. Modeling of scattering by objects on the seabed. The Journal of the Acoustical Society of America, 104 :3296, 1998.
[FG82] RE Francois and GR Garrison. Sound absorption based on ocean mea-surements. part ii : Boric acid contribution and equation for total ab-sorption. The Journal of the Acoustical Society of America, 72 :1879, 1982.
[FM05] John A Fawcett and Vincent L Myers. Computer-aided classification for a database of images of minelike objects. Technical report, DTIC Document, 2005.
[Fol96] James D Foley. Computer graphics : Principles and practice, in C, volume 12110. Addison-Wesley Professional, 1996.
[Fre62] A Freedman. A mechanism of acoustic echo formation. Acustica, 12(1) :10–21, 1962.
[GB95] OOMMEN George and RAJENDAR Bahl. Simulation of backscattering of high frequency sound from complex objects and sand sea-bottom. Oceanic Engineering, IEEE Journal of, 20(2) :119–130, 1995.
[GCVE10] J Groen, E Coiras, J Del Rio Vera, and B Evans. Model-based sea mine classification with synthetic aperture sonar. IET radar, sonar & navigation, 4(1) :62–73, 2010.
[Gen89] M. Gensane. A statistical study of acoustic signals backscattered from the sea bottom. In Proceedings Oceanic Engineering, IEEE Journal, volume 14, pages 84 – 93. IEEE, 1989.
[Gro06] Johannes Groen. Adaptive motion compensation in sonar array proces-sing. PhD thesis, Université de Technologie de Delft, 2006.
[GSG07] Didier Gueriot, Christophe Sintes, and Rene Garello. Sonar data si-mulation based on tube tracing. In OCEANS 2007-Europe, pages 1–6. IEEE, 2007.
[GSG11] SN Geethalakshmi, P Subashini, and Mrs P Geetha. A study on detec-ting and classifying underwater mine like objects using image processing techniques. International Journal on Computer Science and Enginee-ring, 3(10), 2011.
[Ham00] E Hammerstad. Backscattering and seabed image reflectivity. EM Tech-nical Note, 2000.
[HBL03] Laurent Hellequin, J-M Boucher, and Xavier Lurton. Processing of high-frequency multibeam echo sounder data for seafloor characterization. Oceanic Engineering, IEEE Journal, 28(1) :78–89, 2003.
[HG04] MP Hayes and PT Gough. Synthetic aperture sonar : A maturing dis-cipline. In Proc. 7th Eur. Conf. Underwater Acoust, pages 1101–1106, 2004.
[HG06] Robert Hickling and Guillermo C Gaunaurd. Comment on paper entit-led,Şan inversion of freedmanŠs Śimage pulseŠmodel in airŤ[j. acoust. soc. am.[bold 119](2), 965–975 (2006)]. The Journal of the Acoustical Society of America, 120 :589, 2006.
[HHW65] John Michael Hammersley, David Christopher Handscomb, and George Weiss. Monte carlo methods. Physics today, 18 :55, 1965.
[Hor59] Joseph Warren Horton. Fundamentals of SONAR. United states naval institute Annapolis, 1959.
[Hun06] Alan Joseph Hunter. Underwater acoustic modelling for synthetic aper-ture sonar. PhD thesis, University of Canterbury. Electrical and Com-puter Engineering, 2006.
[JA] Timothy J. and Ph.D. Alavosus. New product developments : Multi-beam, bathymetry, and auv side scan sonar advances in seafloor map-ping. Technical report, Sonar Products L-3 Klein Associates.
[Jac94] DR Jackson. Apl-uw high-frequency ocean environmental acoustic mo-dels handbook. Applied Physics Laboratory, University of Washington, Technical Report, 9407, 1994.
[Jan] http ://www.janes.com/.
[JAN87] Didier JAN. Traitement d’images numerique applique aux sonars a haute resolution. 11ème Colloque sur le traitement du signal et des images, 1987, pages 357–360, 1987.
[Jen94] Finn Brunn Jensen. Computational ocean acoustics. Springer, 1994. [Jen95] Henrik Wann Jensen. Importance driven path tracing using the photon
map. In Rendering Techniques’ 95, pages 326–335. Springer, 1995. [JWI86] Darrell R Jackson, Dale P Winebrenner, and Akira Ishimaru.
Applica-tion of the composite roughness model to high-frequency bottom backs-cattering. The Journal of the Acoustical Society of America, 79 :1410, 1986.
[K+62] Joseph Bishop Keller et al. Geometrical theory of diffraction. The Journal of the Optical Society of America, 1962.
[Ker51] Donald E Kerr. Propagation of short radio waves, volume 24. IET, 1951.
[Ker94] G Kervern. Applying physical acoustics to near-seafloor object echo-structure estimation. Le Journal de Physique IV, 4(C5) :C5–1277, 1994. [KFCS99] Lawrence E Kinsler, Austin R Frey, Alan B Coppens, and James V
Sanders. Fundamentals of acoustics, volume 1. Wiley-VCH, 1999. [KJM04] B Kapralos, M Jenkin, and E Milios. Sonel mapping : Acoustic modeling
utilizing an acoustic version of photon mapping. In Haptic, Audio and Visual Environments and Their Applications, 2004. HAVE 2004. Pro-ceedings. The 3rd IEEE International Workshop on, pages 1–6. IEEE, 2004.
[KJM05a] Bill Kapralos, M Jenkin, and E Milios. Acoustical diffraction modeling utilizing the huygens-fresnel principle. In Haptic Audio Visual Environ-ments and their Applications, 2005. IEEE International Workshop on, pages 6–pp. IEEE, 2005.
[KJM05b] Bill Kapralos, M Jenkin, and Evangelos Milios. Acoustical modeling using a russian roulette strategy. In Proceedings of the 118th Convention of the Audio Endgineering Society, pages 28–31, 2005.
[KJM08] Bill Kapralos, Michael Jenkin, and Evangelos Milios. Sonel map-ping : a probabilistic acoustical modeling method. Building Acoustics, 15(4) :289–313, 2008.
[KTN12] Naveen Kumar, Qun Feng Tan, and Shrikanth S Narayanan. Object classification in sidescan sonar images with sparse representation tech-niques. In Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on, pages 1333–1336. IEEE, 2012. [Lap09] Pierre-Simon Laplace. Supplément au mémoire sur les approximations
des formules qui sont fonction de très grands nombres. Mémoires de l’Académie Royale des sciences de Paris, 1810 :559–565, 1809.
[LB13] D Legland and J Beaugrand. Automated clustering of lignocellulosic fibres based on morphometric features and using clustering of variables. Industrial Crops and Products, 45 :253–261, 2013.
[LC86] L Le Cam. The central limit theorem around 1935. Statistical science, 1(1) :78–91, 1986.
[LC04] Gilles Le Chenadec. Analyse de descripteurs énergétiques et statistiques de signaux sonar pour la caractérisation des fonds marins. PhD thesis, Université de Bretagne Occidentale, 2004.
[Leg11] Michel Legris. Systèmes sonars de bathymétrie et d’imagerie. Technical report, ENSIETA, 2011.
[Leg12] Michel Legris. Systèmes avancés en acoustique sous-marine. Technical report, ENSIETA, 2012.
[Leo12] Isabelle Leonard. Reconnaissance des objets manufacturés dans des vi-déos sous-marines. PhD thesis, Université de Bretagne Occidentale. Traitement de l’information, 2012.
[Lur98] Xavier Lurton. Acoustique sous-marine : présentation et applications, 1998.
[Lur02] Xavier Lurton. An introduction to underwater acoustics : principles and applications. Springer, 2002.
[Lur10] Xavier Lurton. An introduction to underwater acoustics : principles and applications. Springer, 2010.
[MA64] C Mo McKinney and CD Anderson. Measurements of backscattering of sound from the ocean bottom. The Journal of the Acoustical Society of America, 36 :158, 1964.
[Mac61] KV Mackenzie. Bottom reverberation for 530-and 1030-cps sound in deep water. The Journal of the Acoustical Society of America, 33 :1498, 1961.
[Mal98] Stephane Mallat. A wavelet tour of signal processing, 1998.
[MC97] Herman Medwin and Clarence S Clay. Fundamentals of acoustical ocea-nography. Access Online via Elsevier, 1997.
[MCPB00] Max Mignotte, Christophe Collet, Patrick Pérez, and Patrick Bouthemy. Hybrid genetic optimization and statistical model based approach for the classification of shadow shapes in sonar imagery. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 22(2) :129–141, 2000. [MCR+08] P-Y Mignotte, E Coiras, H Rohou, Y Petillot, J Bell, and K Lebart. Adaptive fusion framework based on augmented reality training. IET Radar, Sonar & Navigation, 2(2) :146–154, 2008.
[MF10] Vincent Myers and John Fawcett. A template matching procedure for automatic target recognition in synthetic aperture sonar imagery. Signal Processing Letters, IEEE, 17(7) :683–686, 2010.
[MG82] Suzanne T McDaniel and Arthur D Gorman. Acoustic and radar sea surface backscatter. Journal of Geophysical Research : Oceans (1978– 2012), 87(C6) :4127–4136, 1982.
[MGM09] Herman Midelfart, Johannes Groen, and Oivind Midtgaard. Template matching methods for object classification in synthetic aperture so-nar images. In Proceedings of the Underwater Acoustic Measurements Conference, 2009.
[MJ89] Pierre D Mourad and Darrell R Jackson. High frequency sonar equa-tion models for bottom backscatter and forward loss. In OCEANS’89. Proceedings, volume 4, pages 1168–1175. IEEE, 1989.
[MJ93] Pierre D Mourad and Darrell R Jackson. A model/data comparison for low-frequency bottom backscatter. The Journal of the Acoustical Society of America, 94 :344, 1993.
[MM10] Herman Midelfart and Øivind Midtgaard. Adaptive template matching for sas images. ECUA 2010, 2010.
[MM11] Herman Midelfart and Øivind Midtgaard. Robust template matching for object classification. In Proc. 4th Underwater Acoustic Measurements Conference, 2011.
[MOS+07] Jacek Marszal, Zawisza Ostrowski, Jan Schmidt, Lech Kilian, Andrzej Jedel, and Aleksander Schmidt. Time variable gain for long range sonar with chirp sounding signal. Hydroacoustics Selected full texts, 10 :117– 122, 2007.
[MW97] Christopher S Meinen and D Randolph Watts. Further evidence that the sound-speed algorithm of del grosso is more accurate than that of chen and millero. The Journal of the Acoustical Society of America, 102 :2058, 1997.
[Mye10] Vincent Myers. Adaptive target classification with imaging sonar as a partially observable markov decision process. Technical report, DTIC Document, 2010.
[PASS07] Ali Pezeshki, Mahmood R Azimi-Sadjadi, and Louis L Scharf. Under-sea target classification using canonical correlation analysis. Oceanic Engineering, IEEE Journal of, 32(4) :948–955, 2007.
[Pau03] C Paul. Underwater acoustic modeling and simulation, 2003.
[Ph.07] Courmontagne Ph. Sas images denoising :the jointly use of an auto adaptive mean filter and the stochastic matched filter. In Electronic Proceedings of OCEANS’07 Aberdeen, 2007.
[Phi09] B Philippe. The handbook of sidescan sonar, 2009.
[PPCB09] Yan Pailhas, Yvan Petillot, Chris Capus, and Keith Brown. Real-time sidescan simulator and applications. In OCEANS 2009-EUROPE, pages 1–6. IEEE, 2009.
[PPLA02] Aleksandra Pizurica, Wilfried Philips, Ignace Lemahieu, and Marc Acheroy. A joint inter-and intrascale statistical model for bayesian wa-velet based image denoising. Image Processing, IEEE Transactions on, 11(5) :545–557, 2002.
[PPS+13] Y Petillot, Y Pailhas, J Sawas, N Valeyrie, and J Bell. Target recognition in synthetic aperture sonar and high resolution side scan sonar using auvs. 2013.
[PRCB06] Yvan Petillot, Scott Reed, Enrique Coiras, and J Bell. A framework for evaluating underwater mine detection and classification algorithms using augmented reality. IEEE journal of Oceanic Engineering, 2006.
[QKSD10] Rebecca T Quintal, John E Kiernan, John Shannon, and Paul S Dysart. Automatic contact detection in side-scan sonar data. In Technologies for Homeland Security (HST), 2010 IEEE International Conference on, pages 270–275. IEEE, 2010.
[QSB+10] B.A.J. Quesson, J.C. Sabel, H. Bouma, R.J. Dekker, and J. Lengrand-Lambert. Automatic target recognition in synthetic aperture sonar images for autonomous mine hunting. ECUA 2010, 2010.
[Qui01] Isabelle Quidu. Classification multi-vues d’un objet immergé à partir d’images sonar et de son ombre portée sur le fond. PhD thesis, Univer-sité de Bretagne occidentale-Brest, 2001.
[RC97] Emmanuelle RICHARD and Jean-Francois CAVASSILAS. Etude d’une classification d’echos sonar fondee sur un traitement sequentiel. In 16 Colloque sur le traitement du signal et des images, FRA, 1997. GRETSI, Groupe d’Etudes du Traitement du Signal et des Images, 1997.
[Ric51] Stephen O Rice. Reflection of electromagnetic waves from slightly rough surfaces. Communications on pure and applied mathematics, 4(2-3) :351–378, 1951.
[Ris96] Philippe Ris. Parallélisation du lancer de rayon par évaluation dyna-mique de la topologie de la scène. PhD thesis, Université de Besançon, 1996.
[RLDV94] R Raillon, A Lhemery, and D De Vadder. Extension du modèle de freed-man de formation des échos au cas transitoire. Le Journal de Physique IV, 4(C5) :C5–829, 1994.
[RPB03] Scott Reed, Yvan Petillot, and Judith Bell. An automatic approach to the detection and extraction of mine features in sidescan sonar. Oceanic Engineering, IEEE Journal of, 28(1) :90–105, 2003.
[RPB04] Scott Reed, Yvan Petillot, and Judith Bell. Model-based approach to the detection and classification of mines in sidescan sonar. Applied optics, 43(2) :237–246, 2004.
[RRCP06] Scott Reed, Ioseba Tena Ruiz, Chris Capus, and Yvan Petillot. The fusion of large scale classified side-scan sonar image mosaics. Image Processing, IEEE Transactions on, 15(7) :2049–2060, 2006.
[RS99] Volker Roth and Volker Steinhage. Nonlinear discriminant analysis using kernel functions. In Advances in neural information processing systems. Citeseer, 1999.
[RTF05] James Riordan, Daniel Toal, and Colin Flanagan. Towards real-time simulation of the sidescan sonar imaging process. In Proceedings of the 4th WSEAS International Conference on Signal Processing, Robotics and Automation, pages 13–15. World Scientific and Engineering Aca-demy and Society (WSEAS), 2005.
[Rud69] Anthony J Rudgers. Acoustic pulses scattered by a rigid sphere immer-sed in a fluid. The Journal of the Acoustical Society of America, 45 :900, 1969.
[Sam01] Gary Steven Sammelmann. Propagation and scattering in very shal-low water. In OCEANS, 2001. MTS/IEEE Conference and Exhibition,